“Draw a bigger circle”

We are approaching the two-year anniversary of Silicon Collar (released on September 2, 2016). Many readers tell me their favorite book I authored is still The New Polymath. Amazon tells me SAP Nation sold the most.

Many disagreed with the thrust of Silicon Collar that automation takes decades to kill jobs. In the interim, automation actually makes workers smarter, speedier and safer. It changes the nature of work and often generates new types of work.

To me, it was one of the most significant books I have written because it reshaped my own approach to work and life. Let me explain.

The Background

When I started to write the book nearly 3 years ago, there was near-panic about machines taking over human jobs. Gartner had projections like “By 2025, three out of 10 jobs will be converted to software, robots or smart machines.” and “By 2018, digital business will require 50% fewer business process workers.” Two Oxford U researchers had an even more pessimistic assessment: “According to our estimates, about 47% of total U.S. employment is at risk.” WEF, McKinsey, MIT and many other thought leaders had similarly large and scary projections about job losses.

I read most of the research and interviewed other market watchers. Very few of them had talked to practitioners who were approving investments in, testing and working alongside automation. Others were one-dimensional – they would only base their research on projections around one type of automation like RPA. Still others appeared politically motivated – wanted more social benefits like Universal Basic Income in their anticipation of catastrophic job losses.

So, I did what Bill Joy (the Sun co-founder among many other things) likes to say “If you cannot solve a problem, make the problem bigger. If you draw a bigger circle, you start to see several systems you can work on.”

I interviewed 50+ practitioners in as many industries/work settings. They told me about machine learning, robotics, drones, wearables, exoskeletons, self-driving vehicles and many other forms of automation. More importantly they told me what worked, what did not, how expensive the machines were. They were pragmatic, not hysterical about the machines they were working with. They told me machines are good at certain tasks, not complete jobs. They told me about unintended consequences – how automation often leads to new, different jobs.

I then spent a lot of time on a very dry subject – data from the Bureau of Labor Statistics. Our labor economy is majestically diverse – supports over 800 occupations. And it is layered – in franchises, on platforms, concentric circles around the Fortune 500, the Federal government etc. – see my posts The Alt-Job economy and The Clover-Leaf Talent economy . I found very few market watchers understand these layers in our complex job economy and so use glib terms like “gig economy”

Most importantly, I spent time looking at automation in the last century – UPC scanners, ATM machines, how cars have been taking over driving from humans. I found UPC codes actually improved inventory control in stores and allowed them to order more SKUs. Sales went up and grocery checkout jobs increased. ATM machines transformed the role of the teller – made them customer service and sales reps. 50 years later, just in the US we still have 90,000 bank branches with over half a million associates. Cars have gradually been self-driving since cruise control was introduced in the 1960s, and yet globally 50% of new cars are still sold with stick shifts.

I concluded in an article called Slow-Motion Automation “… societies absorb automation at a pace that’s much slower than technology’s evolution. And five powerful “circuit breakers” help delay and influence the trajectory of automation in surprising ways.”

People call me a luddite for not accepting machines are becoming faster and killing jobs. I accept that technology progress is accelerating, but its societal adoption is not accelerating and the impact on jobs is still pretty gradual.

So, how has the book research changed me personally?

Made me curious about what people do every day

Like most people, I knew from my neighbors, friends and clients we worked in oh, 30-40 occupations – attorneys, brokers etc. When I wrote The New Polymath in 2010 I thought I had researched a wide range of occupations that Renaissance Men excel at. The BLS data opened my eyes to our much, much larger set of occupations.

Now, when I watch a movie like Arrival, I observe that the Amy Adams character is a linguist who is fluent in Portuguese, Farsi, Sanskrit and Urdu and is qualified to decode alien language. Or that the Matt Damon character in The Martian is a botanist and as he says he literally has to “science the shit” to survive. I enjoy meeting with Mike Rowe and watching his Dirty Jobs episodes which highlight jobs we don’t even know existed. When I meet a Phil Manougian at the National Hurricane Center, I like learning trivia that he is a NOAA Commissioned Corps Officer. It is one of 7 Federal Uniformed Services (others are Army, Marines, Navy, Air Force, Coast Guard and Public Health Service). When I go to a National Park, I seek out Park Rangers. Each has a fascinating story about his/her career path and all kinds of anecdotes from the wild. On flights, I am genuinely curious about what my neighbors do for a living. If they are willing to talk, I listen especially if they happen to be metallurgists, geneticists or in other occupations I don’t encounter on a regular basis.

Made me more cautious about academia and analysts

I was shocked that the Oxford study I mentioned above had been cited and repeated in over 600 other academic publications, none of which chose to point out the flaws in the methodology as I had in the book. 5 years after their scary projections, not a single job has been lost and yet they have not chosen to reverse their study. Given the immense influence Oxford has, I find that irresponsible. At least, Gartner has backed off from its own pessimistic projections.

Now when I see a widely cited analyst and academic study on any subject I check to see if people have truly kicked its tires.

Made me much more interested in “history of work”

Like most technologists I like to look ahead, not back. I have written plenty about the “Future of Work”. Silicon Collar forced me to do a lot of research on automation which originated in the last century – how it originated, how it gradually got adopted, the societal impact it had. The book made me go back and study the evolution of occupations. I wrote “In fact, many of us continue with names which reflect the trades of our ancestors. It could be the Chinese Chong (derived from bow maker), the English Weaver, the Egyptian El-Mofti (from Arabic for legal expert), German Baumgartner (related to orchard), or the Indian Bhattacharya (from Sanskrit for teacher)—and there are thousands of other names derived from occupations in various societies.”

For my next book, I have been reading a lot about how the US tamed its West in the 1800s. Again there, my keen interest is in how occupations evolved. There I am learning about Meriwether Lewis and his already wide set of skills when President Thomas Jefferson picked him to lead the Corps of Discovery. Then the President arranged for him to get a crash education in many other disciplines “Andrew Ellicott taught Lewis map making and surveying. Benjamin Smith Barton tutored Lewis in botany, Robert Patterson in mathematics, Caspar Wistar in anatomy and fossils, and Benjamin Rush in medicine.”

It is fascinating to read about our Mountain Men and their mapping and trapping skills. About our whalers and how the light bulb affected their fortunes. Or our cowboys who arbitraged and moved cattle from Texas to the rail junction in Kansas for sale in Chicago and the Northeast. The early logistics pioneers at firms like Russell, Majors and Waddell who outfitted the oxen wagons the pioneers took west, and the Pony Express, the “human telegraph”. So many colorful occupations adorn our history books. Did you know Sam Clemens aka Mark Twain was a steamboat pilot for a couple of years in the 1850s on the Mississippi river before his writing career took off ? Granted he was fictional, but does Captain Ahab not intrigue you about what a real whaler’s life was like when the book was written around the same time?

So, in balance I continue to be fascinated by the ever evolving job economy. We have a choice of 840 occupations the BLS is tracking. The list will be updated in 2018 and I expect it will be longer and have more STEM influence. Our workers are getting 2nd, 3rd, later acts in life. No other country has so many new gen opportunities — franchises (about 7 million jobs), platforms (Apple, Amazon fulfillment, eBay work at home, Uber etc — about 20 million part time for now but rapidly changing ), new services — alternative healthcare, ethnic groceries, pet/child care etc.(another 5 million). I am not even including Silicon Valley type entrepreneurship opportunities in energy, space, food, IT etc.

Yes, lifetime employment and pensions are elusive, but we have ended up with a remarkable new labor economy that our parents would have drooled to be part of. The book research convinced me what a great time it is to be alive and working.

Comments

“Draw a bigger circle”

We are approaching the two-year anniversary of Silicon Collar (released on September 2, 2016). Many readers tell me their favorite book I authored is still The New Polymath. Amazon tells me SAP Nation sold the most.

Many disagreed with the thrust of Silicon Collar that automation takes decades to kill jobs. In the interim, automation actually makes workers smarter, speedier and safer. It changes the nature of work and often generates new types of work.

To me, it was one of the most significant books I have written because it reshaped my own approach to work and life. Let me explain.

The Background

When I started to write the book nearly 3 years ago, there was near-panic about machines taking over human jobs. Gartner had projections like “By 2025, three out of 10 jobs will be converted to software, robots or smart machines.” and “By 2018, digital business will require 50% fewer business process workers.” Two Oxford U researchers had an even more pessimistic assessment: “According to our estimates, about 47% of total U.S. employment is at risk.” WEF, McKinsey, MIT and many other thought leaders had similarly large and scary projections about job losses.

I read most of the research and interviewed other market watchers. Very few of them had talked to practitioners who were approving investments in, testing and working alongside automation. Others were one-dimensional – they would only base their research on projections around one type of automation like RPA. Still others appeared politically motivated – wanted more social benefits like Universal Basic Income in their anticipation of catastrophic job losses.

So, I did what Bill Joy (the Sun co-founder among many other things) likes to say “If you cannot solve a problem, make the problem bigger. If you draw a bigger circle, you start to see several systems you can work on.”

I interviewed 50+ practitioners in as many industries/work settings. They told me about machine learning, robotics, drones, wearables, exoskeletons, self-driving vehicles and many other forms of automation. More importantly they told me what worked, what did not, how expensive the machines were. They were pragmatic, not hysterical about the machines they were working with. They told me machines are good at certain tasks, not complete jobs. They told me about unintended consequences – how automation often leads to new, different jobs.

I then spent a lot of time on a very dry subject – data from the Bureau of Labor Statistics. Our labor economy is majestically diverse – supports over 800 occupations. And it is layered – in franchises, on platforms, concentric circles around the Fortune 500, the Federal government etc. – see my posts The Alt-Job economy and The Clover-Leaf Talent economy . I found very few market watchers understand these layers in our complex job economy and so use glib terms like “gig economy”

Most importantly, I spent time looking at automation in the last century – UPC scanners, ATM machines, how cars have been taking over driving from humans. I found UPC codes actually improved inventory control in stores and allowed them to order more SKUs. Sales went up and grocery checkout jobs increased. ATM machines transformed the role of the teller – made them customer service and sales reps. 50 years later, just in the US we still have 90,000 bank branches with over half a million associates. Cars have gradually been self-driving since cruise control was introduced in the 1960s, and yet globally 50% of new cars are still sold with stick shifts.

I concluded in an article called Slow-Motion Automation “… societies absorb automation at a pace that’s much slower than technology’s evolution. And five powerful “circuit breakers” help delay and influence the trajectory of automation in surprising ways.”

People call me a luddite for not accepting machines are becoming faster and killing jobs. I accept that technology progress is accelerating, but its societal adoption is not accelerating and the impact on jobs is still pretty gradual.

So, how has the book research changed me personally?

Made me curious about what people do every day

Like most people, I knew from my neighbors, friends and clients we worked in oh, 30-40 occupations – attorneys, brokers etc. When I wrote The New Polymath in 2010 I thought I had researched a wide range of occupations that Renaissance Men excel at. The BLS data opened my eyes to our much, much larger set of occupations.

Now, when I watch a movie like Arrival, I observe that the Amy Adams character is a linguist who is fluent in Portuguese, Farsi, Sanskrit and Urdu and is qualified to decode alien language. Or that the Matt Damon character in The Martian is a botanist and as he says he literally has to “science the shit” to survive. I enjoy meeting with Mike Rowe and watching his Dirty Jobs episodes which highlight jobs we don’t even know existed. When I meet a Phil Manougian at the National Hurricane Center, I like learning trivia that he is a NOAA Commissioned Corps Officer. It is one of 7 Federal Uniformed Services (others are Army, Marines, Navy, Air Force, Coast Guard and Public Health Service). When I go to a National Park, I seek out Park Rangers. Each has a fascinating story about his/her career path and all kinds of anecdotes from the wild. On flights, I am genuinely curious about what my neighbors do for a living. If they are willing to talk, I listen especially if they happen to be metallurgists, geneticists or in other occupations I don’t encounter on a regular basis.

Made me more cautious about academia and analysts

I was shocked that the Oxford study I mentioned above had been cited and repeated in over 600 other academic publications, none of which chose to point out the flaws in the methodology as I had in the book. 5 years after their scary projections, not a single job has been lost and yet they have not chosen to reverse their study. Given the immense influence Oxford has, I find that irresponsible. At least, Gartner has backed off from its own pessimistic projections.

Now when I see a widely cited analyst and academic study on any subject I check to see if people have truly kicked its tires.

Made me much more interested in “history of work”

Like most technologists I like to look ahead, not back. I have written plenty about the “Future of Work”. Silicon Collar forced me to do a lot of research on automation which originated in the last century – how it originated, how it gradually got adopted, the societal impact it had. The book made me go back and study the evolution of occupations. I wrote “In fact, many of us continue with names which reflect the trades of our ancestors. It could be the Chinese Chong (derived from bow maker), the English Weaver, the Egyptian El-Mofti (from Arabic for legal expert), German Baumgartner (related to orchard), or the Indian Bhattacharya (from Sanskrit for teacher)—and there are thousands of other names derived from occupations in various societies.”

For my next book, I have been reading a lot about how the US tamed its West in the 1800s. Again there, my keen interest is in how occupations evolved. There I am learning about Meriwether Lewis and his already wide set of skills when President Thomas Jefferson picked him to lead the Corps of Discovery. Then the President arranged for him to get a crash education in many other disciplines “Andrew Ellicott taught Lewis map making and surveying. Benjamin Smith Barton tutored Lewis in botany, Robert Patterson in mathematics, Caspar Wistar in anatomy and fossils, and Benjamin Rush in medicine.”

It is fascinating to read about our Mountain Men and their mapping and trapping skills. About our whalers and how the light bulb affected their fortunes. Or our cowboys who arbitraged and moved cattle from Texas to the rail junction in Kansas for sale in Chicago and the Northeast. The early logistics pioneers at firms like Russell, Majors and Waddell who outfitted the oxen wagons the pioneers took west, and the Pony Express, the “human telegraph”. So many colorful occupations adorn our history books. Did you know Sam Clemens aka Mark Twain was a steamboat pilot for a couple of years in the 1850s on the Mississippi river before his writing career took off ? Granted he was fictional, but does Captain Ahab not intrigue you about what a real whaler’s life was like when the book was written around the same time?

So, in balance I continue to be fascinated by the ever evolving job economy. We have a choice of 840 occupations the BLS is tracking. The list will be updated in 2018 and I expect it will be longer and have more STEM influence. Our workers are getting 2nd, 3rd, later acts in life. No other country has so many new gen opportunities — franchises (about 7 million jobs), platforms (Apple, Amazon fulfillment, eBay work at home, Uber etc — about 20 million part time for now but rapidly changing ), new services — alternative healthcare, ethnic groceries, pet/child care etc.(another 5 million). I am not even including Silicon Valley type entrepreneurship opportunities in energy, space, food, IT etc.

Yes, lifetime employment and pensions are elusive, but we have ended up with a remarkable new labor economy that our parents would have drooled to be part of. The book research convinced me what a great time it is to be alive and working.